Lee, GM, Chen, Y, Shu, L and Crespi, N (2016) Industrial Internet of Things based Collaborative Sensing Intelligence: Framework and Research Challenges. Sensors, 16 (2). ISSN 1424-8220

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Abstract

The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a Collaborative Sensing Intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed as well.

Item Type:	Article
Uncontrolled Keywords:	0301 Analytical Chemistry, 0906 Electrical And Electronic Engineering
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science & Mathematics
Publisher:	MDPI
Date Deposited:	05 Feb 2016 13:55
Last Modified:	03 Sep 2021 20:49
URI:	https://researchonline.ljmu.ac.uk/id/eprint/2843

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